標題: | 禪坐組與控制組於心智壓力測試下的腦電波空間非線性相關性 EEG spatially nonlinear interdependence of Chan-meditation practitioners and normal subjects under mental stress test |
作者: | 林永泰 黃經堯 羅佩禎 電子研究所 |
關鍵字: | 腦電波、相似度指標、相位空間重建法;Nonlinear-interdependence |
公開日期: | 2012 |
摘要: | 一些研究報告指出,人的大腦處在邏輯思考及計算推理的狀態下,腦電波所表現出來的頻率將會比放鬆狀態時來的高頻。然而大腦各部位所負責的功能也不盡相同。故本篇論文研究觀點,將放在屬於腦電波比較高頻的Beta band部分,在大腦處於邏輯思考、計算推理狀態下,研究大腦空間交互作用的趨勢及方向。加上有禪定經驗的狀態做比較,進而加以分析禪定對於中樞神經系統的影響。首先我將利用頻域分析來初步判斷腦電波在各頻帶中的能量,進而觀察Beta波的分布情形。接著藉由量化相似度指標與相位空間重建法所發展出來的Nonlinear - Interdependence作為研究與評估。
實驗選取部分,包含了8位接受過禪定者 (實驗組) 與8位無禪定經驗者 (控制組) 做進一步的研究。實驗流程部分,可將實驗組分為三個階段:第一階段數學心算(5-min)、禪定(30-min)、第二階段數學心算(5-min)。而對控制組亦分為三階段:第一階段數學心算(5-min)、閉眼放鬆休息(30-min)、第二階段數學心算(5-min)。
這次研究中探討的腦區,我將大略區分為 : Frontal、 Parietal、 Right-temporal、Left-temporal、 Central等五區,以研究其空間交互作用的關係與結果。 Clinical study has demonstrated that EEG under mental stress has higher frequency than relaxation EEG. This thesis is aimed to investigate the effects of Chan meditation on brain electrophysiological behaviors from the viewpoint of nonlinear interdependence among regional neural networks. Particular emphasis was laid on the EEG beta band. Frequency-domain analysis was adopted to extract beta power. Then nonlinear interdependent measurement based on quantification of similarity index S was applied to the nonlinear dynamical phase-space brain model reconstructed from multi-channel EEG. Experimental and control group involved respectively eight experienced Chan meditation practitioners and eight healthy control subjects. For the experimental group, nonlinear interdependence was evaluated for the brain dynamics under three different stages, pre-meditation background (5-min), Chan meditation (30-min) and post-meditation relaxation (5-min). For the control group, nonlinear interdependence was evaluated for the brain dynamics under three different stages, pre-rest background (5-min), rest (30-min) and post-rest relaxation (5-min). Nonlinear interdependence interaction among various cortical regions was explored for five regions of local neural networks, including: Frontal, Parietal, Right temporal, Left temporal and Central regions. In this study, we find particular interaction between Frontal and Parietal region in all three stages. |
URI: | http://140.113.39.130/cdrfb3/record/nctu/#GT079811683 http://hdl.handle.net/11536/46848 |
顯示於類別: | 畢業論文 |